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QUIC-DEPDOSE is a software application that calculates radiation doses from inhalation of radionuclides downstream from an atmospheric radiological release. Unlike other radiological modeling software, QUIC-DEPDOSE can provide accurate dose information in as little as an hour running on a regular laptop, allowing for use by emergency responders after an accident.
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In this presentation, the speaker discusses the research that has been carried out at NETL regarding direct lithium extraction. The three main discussing points are as follows: developing high-capacity lithium-ion sieve sorbent using mineral streams associated with critical minerals; demonstrating the sorbent ability to recover lithium from oil/gas produced waters and geothermal brines; and assessing the feasibility of large-scale implementation through technoeconomic analysis.
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In a collaborative effort between Hunter College (HC), Lawrence Livermore National Laboratory (LLNL), and Michigan State University (MSU), we aimed to investigate the recovery of 88 Zr produced as the secondary beam at the National Superconducting Cyclotron Laboratory (NSCL) from solid collectors via solid isotope harvesting. We developed separation schemes to isolate Zr from sub-gram-scale collectors composed of various materials including carbon, aluminum, copper, tungsten, and gold. The solid harvesting endstation was constructed and then used as part of a dedicated beamtime at the NSCL using 88 Zr beam. After irradiation, the 88 Zr was radiochemically separated from each of the collector materials and the recovery efficiencies from each was assessed. The results of this work provide a path forward for harvesting hydrolysable metals at FRIB as a complementary approach to aqueous isotope harvesting.
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GCAM's current base year – the last historical year used for calibration – 2015, is considerably lagged compared to the present year, indicating out-of-date assumptions about near-past state of the resources, commodities, and technologies represented in GCAM. This proposal makes data and code changes to enable updating the GCAM base year easier by making the processing code more flexible and robust.
In this project, the scanning electron microscopy (SEM) sampling method used during the statistical design study (SDS) was investigated to determine if any sampling biases were present in the analyzed data. Using standard particle size distribution powders from the National Institute of Standards and Technology (NIST 1984 standard reference material) with the origin wet dispersion method, it was determined that a bias to smaller particles was present. This was supported by theoretical calculations using Stokes’ law to determine the settling rate of spherical particles of roughly the same size and mass as those found in the SDS. Based on the theoretical calculations, it was determined that the settling rate for each of the 76 powder sets in the SDS could be unique based on specific particle shape and mass distributions, making a universal correction factor/formula not applicable. Therefore, priority shifted to developing an improved wet dispersion method that significantly reduced the particle settling rate for all particle size and shapes. This was achieved by replacing the original solvent (isopropyl alcohol) with a heavy liquid (lithium heteropolytungstates), which dramatically slowed the settling rate and allowed for the capture of a suitable homogeneous aliquot. SEM imaging and Morphological Analysis for Material Attribution (MAMA) software analysis were conducted on the NIST standard, and the SEM/MAMA data were compared to data captured by a dynamic image analysis particle size analyzer. The resulting data confirmed that the new wet dispersion method does indeed deliver an improved representative aliquot to the SEM stub. For instance, in the NIST certificate, the average particle size is ~17.1 µm ± 2.2 µm with a normal distribution. The initial wet dispersion method resulted in a drastically reduced average particle size of 6.1 µm in addition to a non-representative heavy bi-modal distribution whereas the improved LST wet dispersion method resulting in an average particle size that was much closer to the NIST certificate (12.7 µm) with a similar normal distribution. Although the improved method was still short of the NIST certificate average, atomic force microscopy analysis determined that the resulting ~20-25% reduction in size was due to particles sinking into the carbon sticky tape used for SEM imaging. It is believed that that this bias can be calibrated in a much more predicable manner than the original settling rate bias. In addition, the matching normal distribution curves between the NIST certificate and the heavy liquid method indicate a much-improved representative aliquot has been sampled and imaged. A surrogate CeO 2 powder was used to reflect PuO 2 more accurately and to aid in implementing radiological controls and shielding. The resulting data sets from the SEM/MAMA method and the particle size analyzer give almost identical average particle sizes and particle distribution statistics. Future work will re-analyze several select runs from the SDS to determine if morphological signatures can be found with the improved sampling method.
This final report summarizes our achievements under the project DE-SC0021158. Briefly, this project allowed us to synthesize using solution chemistry methods and study multinary metal halides. Furthermore, we showed that optical spectroscopy methods in combination with Small Angle X-ray Scattering (SAXS) and Electrospray Ionization Mass Spectrometry (ESI-MS) can be used to discover brand new optical and electronic materials in .
The goal of this internship is to develop a fluid dynamics characterization of the high-pressure flow used for cleaning the internal surface of the SRF cavities. Initially, the High Pressure Rinsing (HPR) process is introduced, focusing on the problems of the SRF cavities and how this method can be used to increase their acceleration efficiency and performance. The characterization of the problem is then presented, including an introduction to the multiphase flow modeling and the analysis of the Fermilab facility for the HPR. To accomplish the goal, a preliminary estimation of the variables was performed using MATLAB. Then, multiple 2D simulations were developed with Ansys Fluent, and the influence of the main parameter was investigated. The simulation results are then presented and analysed, with a focus on the possible future developments of the HPR process fluid dynamic characterization.
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